If we follow blogs and publications on the technological advancement with respect to SQL, we notice the increase in the number of references to Python, of late. Often, that makes us think:
- Why so much emphasis on Python these days?
- Isn’t knowing PowerShell scripting sufficient for the automation requirements of today?
- Is it the time DBAs started learning a programming language such as Python in order to handle their day-to-day tasks more efficiently?
- Why do so many job postings these days include “knowledge of scripting” as a requirement?
- Is all of this happening because the paradigm is shifting? Can’t the current Microsoft-specific languages such as PowerShell handle the shift?
When SQL 2017 was released, it made database administrators raise their eyebrows about two things:
- SQL Server became a cross-platform product
- SQL Server started supporting the enrichment of Machine Learning capabilities
While TSQL, as well as PowerShell cmdlets, are flexible enough to make database activities smoother, making the platform a versatile one, the growing importance of SQL, and the product opening up to Linux enabled more administrators to start looking into what SQL can offer.
Python is a versatile language, when it comes to working with analytical tools, and is considered one of the best available languages in the context. Python is, in fact, fully capable of interacting with huge volumes of data, handling complex mathematics and data manipulation/cleaning.
“OK, so Python is one of the favorite languages used by Linux admins. But hasn’t PowerShell been open-sourced under the MIT License and made available for Linux as well? Has it not already help with using SQL on Linux? Why add support for Python as well? How are we to get started there?”
As it turns out, Python isn’t difficult to learn. Also, learning Python is another arrow added to the quiver. Why not have the additional capabilities, keeping with the spirit of openness? Let’s get started and see how some of our regular tasks can be implemented using Python
Please share your thoughts in the comments section. I would love to hear and learn from you as well.
Thanks for reading my space!